Comprehensive Economic Capital and Credit Risk Modelling Certification Training

This is an advanced professional program designed for risk management, credit risk, and analytics professionals seeking a deep, practical understanding of economic capital frameworks and credit risk modelling used in modern financial institutions. This course provides an integrated look at how credit risk models support key risk functions - from estimating risk parameters and validating models to linking them with regulatory capital, provisioning (CECL/IFRS 9), stress testing, and strategic decision-making.

Participants will explore foundational concepts such as probability of default (PD), loss given default (LGD), and exposure at default (EAD), and how these feed into economic capital and portfolio credit risk measurement under Basel III/IV. Comprehensive coverage of model development, validation standards, macroeconomic scenario design, advanced analytical methods (including machine learning), and practical case studies ensures that learners gain frameworks and tools that they can immediately apply in real-world risk management settings.

Module 1 - Credit Risk & Economic Capital: Foundations and 2025 Context

• Role of credit risk modelling in enterprise risk management
• How credit models support lending, pricing, provisioning, stress testing and capital
• Overview of PD, LGD and EAD fundamentals
• Economic capital vs regulatory capital (Basel III/IV updates)
• Interaction between ICAAP, stress testing, CECL/IFRS 9 and economic capital frameworks
• Post-CECL modelling environment and current supervisory expectations



Module 2 - CECL Methodology & Implementation Challenges (2019-2025)

• Core CECL concepts: lifetime expected loss and reasonable & supportable forecasts
• Transition from incurred-loss to expected-loss models
• Practical challenges since CECL go-live:
  • Segmentation and data limitations
  • Qualitative factors (Q-factors)
  • Scenario design and macroeconomic forecasting
• Current regulatory expectations and common validation findings
• Best practices for model maintenance and stability (2024–2025)



Module 3 - Credit Risk Modelling Frameworks (PD, LGD, EAD)

• PD model development: scoring, ratings, calibration and overrides
• LGD modelling: downturn LGD, collateral treatment and haircuts
• EAD models: credit conversion factors and utilisation modelling
• Behavioural and survival modelling
• Transition matrices and Markov models
• Low-default portfolio (LDP) modelling approaches



Module 4 - Model Development Process & Validation Standards

• End-to-end model development lifecycle
• Feature engineering and model selection
• Back-testing, benchmarking and challenger models
• Model Risk Management (MRM) frameworks aligned with SR 11-7 principles
• Governance, documentation and independent validation standards



Module 5 - Economic Capital Modelling & Portfolio Credit Risk

• Economic capital architecture for credit portfolios
• Credit portfolio models:
  • CreditMetrics
  • KMV / EDF
  • CreditRisk+
• Modelling correlation and systematic risk factors
• Concentration risk measurement
• Stress economic capital vs base-case economic capital
• Linking economic capital to pricing (RAROC) and strategic planning



Module 6 - Forward-Looking Credit Risk, Macro Modelling & Scenario Design

• Incorporating forward-looking macroeconomic variables into credit models
• Managing non-linearity and regime shifts in macro–credit relationships
• Scenario design: baseline, adverse and severe cases
• Scenario overlays and adjustments
• Ensuring consistency across CECL, ICAAP and stress testing



Module 7 - Adjustments, Overlays & Management Judgement

• Purpose of overlays and qualitative adjustments
• Frameworks for determining when overlays are required
• Evidence, documentation, transparency and supervisory scrutiny
• Ensuring overlays integrate properly with model outputs
• Avoiding double counting and maintaining model integrity



Module 8 - Machine Learning & Advanced Analytical Methods (2025 Edition)

• ML and AI applications in PD scoring and early-warning indicators
• Hybrid modelling: combining ML with traditional statistical approaches
• Explainability and regulatory expectations for XAI
• Ethical fairness, bias control and governance in ML credit models
• Suitability of ML for CECL and economic capital workloads



Module 9 - Stress Testing & Enterprise Integration of Credit Models

• Types of credit stress tests: sensitivity, scenario-based and reverse stress testing
• Portfolio-level credit stress design and expansion
• Integrating credit models into ICAAP and capital planning
• Stress-testing linkages with risk appetite frameworks
• Adjusting CECL and economic capital estimates under stress



Module 10 - Case Studies, Practical Exercises & Final Assessment

• PD, LGD and EAD modelling using sample datasets
• CECL lifetime loss estimation walkthrough
• Economic capital computation for a sample credit portfolio
• Scenario-based portfolio impact simulation
• Final certification assessment (knowledge test and practical application)

• Basic understanding of finance, banking or risk management concepts
• Familiarity with credit products, lending and balance-sheet principles
• Comfort with numerical and analytical reasoning
• No prior experience with CECL or economic capital models is required

• Credit risk analysts and managers
• Risk management professionals involved in ICAAP, CECL, IFRS 9 or stress testing
• Finance professionals supporting credit portfolio management or capital planning
• Internal audit and model validation teams focused on credit risk models
• Senior management and decision-makers who rely on credit risk metrics for strategy

• 20 multiple-choice questions covering all course modules
• Passing requirement: at least 15 correct answers
• Two attempts allowed to achieve a passing score
• Certificate issued upon successful completion of the exam

Obtaining the Comprehensive Economic Capital and Credit Risk Modelling Certification with training provides professionals with the in-depth knowledge and practical skills necessary to understand and apply advanced risk modelling techniques. This training goes beyond basic concepts by teaching participants how to develop and calibrate economic capital models, assess credit risk exposures and integrate these models into the broader risk management and decision-making processes within financial institutions. The course includes coverage of key topics such as credit migration, stress testing, scenario analysis, loss given default (LGD), probability of default (PD), and expected loss (EL), making it ideal for credit analysts, risk managers, portfolio managers and financial engineers who are involved in credit risk analysis and capital management.

From a career and financial perspective, earning this certification with structured training significantly enhances professional credibility, marketability and earning potential. With increased regulatory scrutiny on financial institutions and an emphasis on strong risk governance, professionals who are proficient in advanced credit risk modelling and economic capital assessment are in high demand. Certified individuals often take on roles such as Credit Risk Modellers, Risk Managers, Financial Engineers or Capital Management Analysts, with annual salaries ranging from $80,000 to $130,000 based on experience and location. Senior or specialised roles in financial institutions may command salaries exceeding $150,000. By combining a recognised certification with practical, scenario-based training, participants not only enhance their technical expertise but also position themselves for leadership roles in risk management and capital strategy.

A FRM and PRM certified Financial Risk Management Consultant with international expertise in risk management methodological frameworks. He brings over 25 years of experience advising financial institutions and organisations on effective risk management practices. Qualified in Islamic Finance (IFQ), he is a published author on risk management and Basel Accords and a regular speaker at industry conferences. In addition, he delivers training courses and workshops for professionals across the globe, helping participants strengthen their risk management knowledge and skills.

Learning Outcomes:

• Explain the role of credit risk modelling within enterprise risk management and its relationship with economic and regulatory capital frameworks.
• Delineate key credit risk parameters - PD, LGD, and EAD - and understand how they inform provisioning, capital and risk measurement.
• Describe the differences between economic capital and regulatory capital, including Basel III/IV implications and interactions with ICAAP and stress testing.
• Develop and validate credit risk models using best practices for scoring, calibration, benchmarks and model risk governance.
• Apply methods for portfolio-level credit risk modelling, including CreditMetrics, CreditRisk+ and KMV/EDF approaches.
• Incorporate forward-looking macroeconomic variables in credit risk estimations and scenario designs for stress testing and capital planning.
• Assess when qualitative adjustments and overlays are appropriate, including documentation and governance for supervisory scrutiny.
• Evaluate advanced analytical techniques, including machine learning applications, while understanding regulatory expectations for explainability and bias control.
• Integrate credit risk modelling outputs into enterprise risk processes, including stress testing, strategic planning and RAROC-based decision frameworks.